An optimal architecture of artificial neural network for predicting compressive strength of concrete

Indian Concrete Journal

Volumn 81, Issue 8, 2007, Pages 17-24

  Noorzaei, J ^a   Hakim, S J S ^d   Jaafar, M S ^b   Abang Ali, A A ^b   Thanoon, Waleed A M ^c  

^a Structural Engineering Research Group   (Malaysia)

^b UPM   (Finland)

^c DEPARTMENT OF CHEMICAL ENGINEERING   (Malaysia)

^d NONE

Author keywords

Artificial Neural Networks (ANNs); Backpropagation (BP); Compressive strength; Mean square error (MSE)

Indexed keywords

COARSE AGGREGATE; DATA POINTS; FEASIBLE TOOLS; SUPERPLASTICISER;

ARCHITECTURE; BACKPROPAGATION; COMPRESSIVE STRENGTH; MEAN SQUARE ERROR; NEURAL NETWORKS; PLASTICIZERS; SILICA;

CONCRETES;

EID: 35648977118     PISSN: 00194565     EISSN: None     Source Type: Trade Journal    
DOI: None     Document Type: Article

References (24)

1. Hakim, S.J.S., Development of artificial neural network for some civil engineering applications, Thesis submitted to Department of Civil Engineering, University Putra Malaysia, Malaysia, December 2006.
2. Noorzaei, J., Jaafar, M.S., Thanoon, W.A.M. and Hakim, S.J.S., Development of an artificial neural network model for prediction of ultimate soil bearing capacity, Proceedings of the eighth international conference on the application of artificial intelligence to civil, structural and environmental engineering, August 2005, pp. 133-134.
3. Yeh, I.C., Modelling of strength of high-performance concrete using artificial neural networks, Journal of Cement and Concrete Research, 1998, Vol. 28, No. 2, pp. 1797-1808.
4. Guang, N.H. and Zong, W.J., Prediction of compressive strength of concrete by neural networks, Journal of Cement and Concrete Research, 2000, Vol. 30, pp. 1245-1250.
5. Dias, W.P.S. and Pooliyadda, S.P., Neural networks for predicting properties of concretes with admixtures, Journal of Construction and Building Materials, 2001, Vol. 15, pp. 371-379.
6. Wang, J.Z., Ni, H.G. and He, J.Y., The application of automatic acquisition of knowledge to mix design of concrete, Journal of Cement and Concrete Research, 1999, Vol. 29, pp. 1875-1880.
7. Kim, J.I., Kim, D.K., Feng, M.Q. and Yazdani, F., Application of neural networks for concrete strength, Journal of Materials in Civil Engineering, 2004, Vol. 16, No. 3, pp. 257-264.
8. Eldin, N.N. and Senouci, A.B., Measurement and prediction of the strength of rubberized concrete, Journal of Cement and Concrete Composites, 1994, Vol. 16, pp. 287-298.
9. Hola, J. and Schabowicz, K., Application of artificial neural networks to determine concrete compressive strength based on non-destructive tests, Journal of Civil Engineering and Management, 2005, Vol. 11, No. 1, pp. 23-32.
10. Lee, S.C., Prediction of concrete strength using artificial neural networks, Journal of Engineering Structures, 2003, Vol. 25, pp. 849-857.
11. Mansour, M.Y., Dicleli, M., Lee, Y.J. and Zhang, J., Predicting the shear strength of reinforced concrete beams using artificial neural networks, Journal of Engineering Structures, 2004, Vol. 26, pp. 781-799.
12. Lai, S. and Serra, M., Concrete strength prediction by means of neural network, Journal of Construction and Building Materials, 1997, Vol. 11, No. 2, pp. 93-98.
13. Adeli, H., Neural networks in civil engineering: 1989-2000, Journal of Computer Aided Civil and Infrastructure Engineering, 2001, Vol. 16, pp. 126-142.
14. Cho, J.H. and Ghaboussi, J., Genetic algorithm in structural damage detection, Journal of Computers and Structures, 2001, Vol. 79, pp. 1335-1353.
15. Hagan, M.T., Demuth, H.B. and Beale, M.H., Neural network design, PWS Publishing Company, 1996, Boston, USA.
16. Lee, M.I. and Lee, H.J., Prediction of pile bearing capacity using artificial neural networks, Journal of computers and Geotechnique, 1996, Vol. 18, No. 3, pp. 189-200.
17. March, P., Concrete as a visual material, Cement and Concrete Association, London, UK, 1974.
18. Dodson, V.H., Concrete Admixtures, Van Nostrand Reinhold, New York, USA, 1990.
19. Mcintosh, J.D., Concrete and Statistics, Maclaren, London, UK, 1968.
20. Hola, J. and Schabowicz, K., New technique of nondestructive assessment of concrete strength using artificial intelligence, NDT&E International Journal, 2004, Vol. 38, pp. 251-259.
21. Pala, M., Ozbay, E., Oztas, A. and Yuce, M.I., Appraisal of long-term effects of fly ash and silica fume on compressive strength of concrete by neural networks, Journal of Construction and Building Materials, 2005, Vol. 21, pp. 384-394.
22. Kasperkiewicz, J., The application of ANNs in certain materials analysis problems, Journal of Materials Processing Technology, 2000, Vol. 106, pp. 74-79.
23. Kasperkiewicz, J., Racz, J. and Dubrawski. A., HPC strength prediction using artificial neural network, Journal of Computing in Civil Engineering, 1995, Vol. 9, No. 4, pp. 279-284.
24. Can, I., A new improved Na/K geothermometer by artificial neural networks, Geothermics, 2002, Vol. 31, pp. 751-760.